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Update app.py
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app.py
CHANGED
@@ -301,6 +301,9 @@ def text_classification_and_sentiment(text, keywords_df):
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sentiment_output = f"Sentiment: {sentiment_label}\nProbability: {sentiment_score * 100:.2f}%"
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decision_output = f"Decision: {decision}"
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return tpb_output, sentiment_output, decision_output
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@@ -382,9 +385,9 @@ with gr.Blocks(css=css + """
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# This needs to be called at some point prior to the first call to callback.flag()
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hf_writer.setup([input_text,tpb_output, sentiment_output], "flagged_data_points")
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classify_button = gr.Button("Analyze")
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classify_button.click(lambda *args: hf_writer.flag(list(args)),fn=text_classification_and_sentiment, inputs=input_text, outputs=[tpb_output, sentiment_output, decision_output])
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gr.Examples(examples=examples, inputs=input_text)
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with gr.TabItem("Company View", id=1):
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sentiment_output = f"Sentiment: {sentiment_label}\nProbability: {sentiment_score * 100:.2f}%"
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decision_output = f"Decision: {decision}"
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hf_writer.flag([text,tpb_output, sentiment_output])
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return tpb_output, sentiment_output, decision_output
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# This needs to be called at some point prior to the first call to callback.flag()
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hf_writer.setup([input_text,tpb_output, sentiment_output], "flagged_data_points")
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classify_button = gr.Button("Analyze")
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classify_button.click(fn=text_classification_and_sentiment, inputs=input_text, outputs=[tpb_output, sentiment_output, decision_output])
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gr.Examples(examples=examples, inputs=input_text)
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with gr.TabItem("Company View", id=1):
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